Unified User Behavior Tracking Across Devices
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Solution Overview
Problem
The proliferation of diverse media devices and platforms makes it difficult for network operators and service providers to collect and analyze comprehensive user behavior data, resulting in a fragmented and incomplete picture of user preferences and habits, which hinders the delivery of customized content experiences.
Innovation Solution
A system and method for tracking user behavior across multiple devices and modalities, normalizing and merging data into a unified clickstream, and generating actionable user behavioral models to inform personalized content recommendations and advertising.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If user behavior data is collected across multiple diverse media devices and platforms, then the quantity and variety of user behavior information is improved, but the complexity of data collection and analysis increases
Solution Approach 1:
The patent introduces a data normalization layer that acts as an intermediary between diverse data sources and the analysis system. This normalization layer standardizes data from multiple devices and platforms into a unified format, reducing the complexity of handling heterogeneous data while preserving the quantity and variety of user behavior information.
Solution Approach 2:
The system implements a universal data collection framework that can handle multiple types of media devices and platforms through a common interface. This multi-functional approach allows the system to collect user behavior data from various sources (TV, computer, mobile devices, etc.) using the same methodology, reducing overall system complexity.
2Loss of information
If comprehensive user behavior data is gathered from distributed sources, then the completeness of user profile is improved, but the difficulty of data normalization and integration increases
Solution Approach 1:
The patent transforms user behavior data from various sources by changing its parameters to a standardized format. The normalization process adjusts data parameters (timestamps, user identifiers, behavior types) to a common reference frame, enabling complete user profiling while reducing integration difficulty through systematic parameter transformation.
Solution Approach 2:
The system segments the data integration process into distinct stages: data collection from individual sources, normalization of each source's data format, and merging of normalized data into a unified user profile. This segmentation makes the overall integration task more manageable while ensuring comprehensive information capture.
3Measurement precision
If user behavior tracking is implemented across multiple devices, then the accuracy of user preference analysis is improved, but the computational resources required increase
Solution Approach 1:
The patent implements selective tracking of user behavior events, focusing on collecting and analyzing only the most relevant data points for preference analysis. By applying partial action (tracking only significant events rather than all possible interactions), the system maintains high analysis accuracy while reducing computational resource consumption.
Solution Approach 2:
The system extracts and focuses on key behavioral patterns and preferences from the comprehensive user data, separating the essential information needed for accurate preference analysis from the broader dataset. This extraction approach maintains measurement precision by concentrating computational resources on the most informative data elements.
Data Source
AI summary
Disclosed herein are systems, methods, and computer readable-media for contextual adaptive advertising. The method for contextual adaptive advertising comprises tracking user behavior across multiple modalities or devices, storing one or more representations of user behavior in a log as descriptors, normalizing the descriptors, merging the normalized descriptors into a unified click or interactive stream, and generating a behavioral model by analyzing the click or interactive stream.